|
|
Absolute deviation, 绝对离差7 P/ _0 @/ {+ \
Absolute number, 绝对数 b% I& p: { m% V0 \
Absolute residuals, 绝对残差
% p; k( P& v; R# x( H* rAcceleration array, 加速度立体阵8 b7 F+ V! }) e* l
Acceleration in an arbitrary direction, 任意方向上的加速度. ]& f3 |% S* r; u
Acceleration normal, 法向加速度2 ]- V4 R0 [4 c
Acceleration space dimension, 加速度空间的维数4 L- q0 ?( g5 N L& K' Y$ C
Acceleration tangential, 切向加速度
& r0 E% ]9 c5 D O" o9 r# CAcceleration vector, 加速度向量 ~0 J8 d8 i/ h1 n! D
Acceptable hypothesis, 可接受假设8 k" p7 v! m9 o7 m. Q! W- M1 R
Accumulation, 累积: P7 O0 H8 U- S# ?, k: u4 L9 e0 l3 H
Accuracy, 准确度4 j' M. W% v& Y5 B
Actual frequency, 实际频数: v' {* M% u% o% |, V
Adaptive estimator, 自适应估计量
- g- j; W3 S* T+ K* |Addition, 相加3 x3 `# k7 c; S1 Q. f
Addition theorem, 加法定理% Q# h+ |) B* \
Additivity, 可加性
4 {! o2 K6 D& S9 z) V( IAdjusted rate, 调整率
' w m D! E; QAdjusted value, 校正值/ V8 a; t# U! H# @( Z% \3 E
Admissible error, 容许误差
6 t- \! V9 `5 [! n% i: eAggregation, 聚集性
) t# m# v9 M( n. N7 Z4 JAlternative hypothesis, 备择假设% t7 o/ o+ x& ]- X& |
Among groups, 组间8 J% \- l6 G0 u
Amounts, 总量
* _8 U) F. l. ? AAnalysis of correlation, 相关分析9 F1 x; n1 T8 R5 ?4 N
Analysis of covariance, 协方差分析# h( j, P" ^0 V9 }8 K& Y9 g
Analysis of regression, 回归分析6 l- h0 o, k! `
Analysis of time series, 时间序列分析; P y+ G: p+ x# I: c$ g! L
Analysis of variance, 方差分析8 w$ N; ?9 |- `3 F& ]9 q% @9 B
Angular transformation, 角转换
( u: g3 B5 W- j" H6 {! a: bANOVA (analysis of variance), 方差分析
; U- i f# P& NANOVA Models, 方差分析模型8 C+ D8 S! n$ `" A
Arcing, 弧/弧旋9 ~$ D% o" t$ E! k
Arcsine transformation, 反正弦变换
8 I4 h& W1 U" @5 EArea under the curve, 曲线面积
+ _( H7 j1 o1 Z+ Z& {9 {AREG , 评估从一个时间点到下一个时间点回归相关时的误差
$ W. d% p5 _0 v+ RARIMA, 季节和非季节性单变量模型的极大似然估计 4 v9 H- ^1 G" S5 s ]. H0 y
Arithmetic grid paper, 算术格纸5 P. r, ?. Z/ B2 b, u4 j% P Y
Arithmetic mean, 算术平均数: [/ W: J/ E5 D7 w1 l v/ \
Arrhenius relation, 艾恩尼斯关系5 n7 Q! a) j' m2 y" f0 \
Assessing fit, 拟合的评估
8 Y9 \3 G0 R& G$ {/ |# v' tAssociative laws, 结合律+ C% J; C1 |4 O. _* T- w* g, |2 a7 H
Asymmetric distribution, 非对称分布
W" Z. p$ P7 o; o* {( ZAsymptotic bias, 渐近偏倚* W# L' \! Z. m9 |& r0 z$ h0 o
Asymptotic efficiency, 渐近效率2 B" |) l0 o& J5 Q5 w7 ?0 g
Asymptotic variance, 渐近方差
|* H y, o2 L( vAttributable risk, 归因危险度7 a* p+ ~+ C/ n2 d* _- I, ]
Attribute data, 属性资料
! w& g6 D% o5 x8 q5 ?: hAttribution, 属性
. k( r# m/ h/ C, {Autocorrelation, 自相关
- d3 o' {% H- M! _8 ~5 o7 sAutocorrelation of residuals, 残差的自相关
% K( B) t" L. J# k/ |. @Average, 平均数
~) o) P7 j1 C8 w* {Average confidence interval length, 平均置信区间长度0 V; O/ d# w* j* J4 w! z6 h1 N
Average growth rate, 平均增长率
. |& S& @$ `. ZBar chart, 条形图- x9 b- {8 w/ [
Bar graph, 条形图& t. \8 c1 K9 P! r0 ]
Base period, 基期$ s* X w% }, U* j4 w
Bayes' theorem , Bayes定理
7 F- @; T0 f* m. Q" t uBell-shaped curve, 钟形曲线
& v6 J' ` g3 g* T/ J& N- c- S" I7 nBernoulli distribution, 伯努力分布# S; [$ Y3 p3 W$ b) G/ H
Best-trim estimator, 最好切尾估计量: s2 k9 H2 @7 A/ b8 R; U; A
Bias, 偏性% p+ _ _0 w' j* ?
Binary logistic regression, 二元逻辑斯蒂回归
+ W) d+ v+ ^) ^: ?: g0 fBinomial distribution, 二项分布
% N# R) S1 F6 M- m- \) S4 HBisquare, 双平方
' ~- U1 \' v5 m0 ^$ k$ n: b* SBivariate Correlate, 二变量相关
- k q7 K* K. x5 t* u6 OBivariate normal distribution, 双变量正态分布% u Q7 Q- T$ g7 C3 E+ r8 r9 T/ m# Y
Bivariate normal population, 双变量正态总体
9 E1 {" @% \% P0 _3 IBiweight interval, 双权区间& n7 F- Z+ W" P8 m% m- p
Biweight M-estimator, 双权M估计量2 {% e8 W4 @ Z
Block, 区组/配伍组
% o& A; O4 X( d' k) `. L, sBMDP(Biomedical computer programs), BMDP统计软件包
% \( ~) V/ _1 nBoxplots, 箱线图/箱尾图
: q+ d* [0 s& M. H: y# a' `Breakdown bound, 崩溃界/崩溃点
) ?# ?( u6 U7 a2 e# @' _! a Q6 oCanonical correlation, 典型相关( I4 o# Q" l+ `* }
Caption, 纵标目3 I" C1 f }0 X% I
Case-control study, 病例对照研究( z: w, I' J! i. V% A6 K
Categorical variable, 分类变量
! N0 G/ }0 F5 B" hCatenary, 悬链线& Q5 n2 Z+ f/ L7 G) i) Q9 X
Cauchy distribution, 柯西分布 C8 g" a/ | V- G y& ?8 p4 f/ l
Cause-and-effect relationship, 因果关系
- V' Z0 l' f% q, r3 E9 G4 ECell, 单元& L! Z; r( y2 a1 @
Censoring, 终检) V0 G: M; E( B0 p# _, g2 h
Center of symmetry, 对称中心
* T3 G) A3 ~" U( YCentering and scaling, 中心化和定标
# u& c0 Y% l' D8 E+ n5 Q0 V) E$ S6 UCentral tendency, 集中趋势4 p s B" ^" t, v( f( q
Central value, 中心值
4 W ?# ^- ~/ f( z g& [ o6 UCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测9 z) J; L# ^( _: U$ v
Chance, 机遇- m; h. v6 v0 G! w1 M/ A
Chance error, 随机误差9 ]# v5 Z7 i j7 v' W, j, S- |$ Y
Chance variable, 随机变量& y5 A' a% Q. ]( n+ m7 q1 ?
Characteristic equation, 特征方程
- M/ X% c9 c( q5 D0 Q cCharacteristic root, 特征根
, L& ]( ^6 @; V$ ~, wCharacteristic vector, 特征向量
7 y$ I+ P, k, u9 y& o$ IChebshev criterion of fit, 拟合的切比雪夫准则
1 U. A' V' {2 e1 ]& u# gChernoff faces, 切尔诺夫脸谱图) {; b: U. D9 Z, D u
Chi-square test, 卡方检验/χ2检验3 p: {4 b! T; H
Choleskey decomposition, 乔洛斯基分解8 K( v. V3 d" D2 A/ t1 B9 d( U$ f
Circle chart, 圆图 * ~; o! U' B3 z( z
Class interval, 组距( u6 Z) y. ?8 b+ ~" ^4 M
Class mid-value, 组中值
, y' D' t( q* s' c+ h9 W$ XClass upper limit, 组上限8 H* j N2 C2 z7 W9 C% a" ?0 x5 f
Classified variable, 分类变量
$ x* b5 T, e3 Q: i7 b: Z; mCluster analysis, 聚类分析; j, D7 B' f& ?7 c) ~* P
Cluster sampling, 整群抽样
4 n/ ]* a7 J( |; z8 GCode, 代码: R5 s7 c; m6 N
Coded data, 编码数据
' k* b [9 B. Y2 K: N# ^Coding, 编码" \6 H( A+ \. ~: l0 [4 ?
Coefficient of contingency, 列联系数/ m$ J; W: @% X( w! j, x/ _* h2 d
Coefficient of determination, 决定系数
: b- _" T7 _* K" B. RCoefficient of multiple correlation, 多重相关系数8 Y2 I3 ]4 b8 a" ~5 p. z- E. {% P
Coefficient of partial correlation, 偏相关系数
8 x# P5 j( N+ M& }5 X ]/ yCoefficient of production-moment correlation, 积差相关系数- b3 D; N( C. E/ ]
Coefficient of rank correlation, 等级相关系数
+ H, U+ `6 z1 P0 kCoefficient of regression, 回归系数
- F' F! C& \8 i7 \Coefficient of skewness, 偏度系数6 i" h4 _& o; f6 m+ |
Coefficient of variation, 变异系数6 g& Z c0 G) l. {: v; h: x+ Q
Cohort study, 队列研究
- H# ?9 k4 |" I: O& u: `& V% o7 uColumn, 列5 [) E3 E7 ^, u [% s! Q _
Column effect, 列效应3 j) Z; E" A; Q! E9 \- m3 G; _
Column factor, 列因素0 w* c8 n4 \$ {/ y) l* `0 l7 F- E" F
Combination pool, 合并 \, {: o* ~+ I' _8 I8 q
Combinative table, 组合表
9 M P1 O6 w. c# t& UCommon factor, 共性因子
& u4 I( s* Q1 c5 t1 d7 X; uCommon regression coefficient, 公共回归系数
+ [; |4 L0 |9 d5 F0 |! }Common value, 共同值& t! L/ ~9 X O: r. D; |" m
Common variance, 公共方差
. |" m4 O$ c, ^9 UCommon variation, 公共变异% o3 S0 R) I( l% m
Communality variance, 共性方差
; H6 ?* ?, L. uComparability, 可比性; M' [8 V) X7 U# [ ^7 m `. m
Comparison of bathes, 批比较# V! t D h* I; X U
Comparison value, 比较值
) M1 g) Y6 t+ F4 D1 SCompartment model, 分部模型1 A' W" t# n, s! C9 Q
Compassion, 伸缩# F/ T" \# t' |0 w" I8 O
Complement of an event, 补事件
/ M; }. \7 e' V) a* i1 ]) JComplete association, 完全正相关% w; \0 s$ h* q7 t3 [
Complete dissociation, 完全不相关
' i6 W. V x {" rComplete statistics, 完备统计量7 t) j: I+ m7 q0 V
Completely randomized design, 完全随机化设计
: w+ ~/ Z: C* CComposite event, 联合事件) U& v- O, E6 W1 Q; l% X
Composite events, 复合事件. [9 F1 h6 _# H1 _9 S
Concavity, 凹性
! |9 j) H+ J" \Conditional expectation, 条件期望
4 c$ @! ?0 U) p# ] G' zConditional likelihood, 条件似然
7 V4 h8 j3 O# tConditional probability, 条件概率
Q) n* }# m" X8 ^! v7 RConditionally linear, 依条件线性( |* f9 }0 ~5 \& J! |5 l% v
Confidence interval, 置信区间
& ~, d4 x1 a) I" _Confidence limit, 置信限8 d& S1 L, R4 T4 C) C5 x: F
Confidence lower limit, 置信下限1 h. k1 X! n- h, ?0 B; ?
Confidence upper limit, 置信上限
1 H: E) y7 V3 d5 A7 oConfirmatory Factor Analysis , 验证性因子分析. E8 {3 d# B s$ K
Confirmatory research, 证实性实验研究
4 ^5 m8 v% R, [3 @# ~. dConfounding factor, 混杂因素2 i- t9 [- j* C7 D. A+ v
Conjoint, 联合分析
" \% P# d: x& q" N$ j5 D& `8 ~4 sConsistency, 相合性; b2 N- e. Y' L4 z' _$ P9 e
Consistency check, 一致性检验$ e' m2 w9 \: p, v
Consistent asymptotically normal estimate, 相合渐近正态估计# Z$ p% \& Y6 f& R1 n
Consistent estimate, 相合估计 W% l7 A7 u% w
Constrained nonlinear regression, 受约束非线性回归) t3 l9 ?9 j* C+ e8 R
Constraint, 约束
, i* j W; v. G4 s' OContaminated distribution, 污染分布- j$ Y1 w0 r& P0 a+ f$ }8 @
Contaminated Gausssian, 污染高斯分布
: \; M Y1 l/ I' e. R# n- d6 b/ BContaminated normal distribution, 污染正态分布+ a' k1 {. |5 s6 o# V3 ?
Contamination, 污染" u2 V9 B, K; R
Contamination model, 污染模型$ g0 X5 }. q' @9 W. r/ _+ N& D7 W. I
Contingency table, 列联表
. q6 R+ Z/ c/ W8 i; a/ ^3 O( @' uContour, 边界线; p4 a& x5 D! Q v
Contribution rate, 贡献率6 A5 r9 R9 h4 T/ t& @ _
Control, 对照
* n; |! ?- Z) P# l; [Controlled experiments, 对照实验8 r. B3 n' v+ f: q/ D* M
Conventional depth, 常规深度
# H) }4 h0 K8 K2 Q- U/ s% hConvolution, 卷积
% p* B) [$ T2 e d/ u% WCorrected factor, 校正因子
$ i, R" B( `$ e7 Q3 | k2 _Corrected mean, 校正均值
1 X5 j+ C }) C1 ~ OCorrection coefficient, 校正系数3 M! F+ N0 f6 T3 e" j& X: R
Correctness, 正确性9 v( B' ]4 k/ R
Correlation coefficient, 相关系数6 L* m8 Y) _# H8 ]( `2 _; s
Correlation index, 相关指数2 ]- [# K* @# E2 y4 k
Correspondence, 对应; X O# K6 p' Q4 N+ N
Counting, 计数
& G( \( R5 M( ?! V, |4 }Counts, 计数/频数
$ u! j+ u. R' C5 ~ Q% J6 pCovariance, 协方差
( T8 m" V3 B1 @9 H+ o; d/ VCovariant, 共变 ( y3 p# R4 r1 \4 H- }- J: T
Cox Regression, Cox回归
+ H# L9 x1 E3 k' a; v, l4 qCriteria for fitting, 拟合准则% k0 Z$ o9 }" f! ~% }
Criteria of least squares, 最小二乘准则# k4 u; Q/ G, V1 ^3 s' x
Critical ratio, 临界比
; I, G. `' u2 w( x9 U: p: XCritical region, 拒绝域6 C+ r% G' f* ]. T6 l
Critical value, 临界值
; \3 d5 |/ b9 v4 kCross-over design, 交叉设计
r3 b* i- i1 s9 h5 n7 ]% FCross-section analysis, 横断面分析
4 g* v" n- R% {: {6 xCross-section survey, 横断面调查" E% O2 H- N1 d* F
Crosstabs , 交叉表 ; {) W7 a+ W/ p8 ~
Cross-tabulation table, 复合表9 @$ F& p9 N5 F
Cube root, 立方根6 J# Y+ E/ C& j3 v3 {
Cumulative distribution function, 分布函数
" I0 o D9 @2 K, ZCumulative probability, 累计概率, R: l% T# @! A6 x; x
Curvature, 曲率/弯曲
4 |8 H' x5 S* }3 P p2 P! nCurvature, 曲率 i7 U) G; L0 m, ?
Curve fit , 曲线拟和 - _/ t% D! J4 L# T" @; ^: B
Curve fitting, 曲线拟合
; o2 N* o( x$ Q2 C2 I, I+ mCurvilinear regression, 曲线回归
$ P* \0 P$ M% E" B8 h0 x( ^6 T6 a5 bCurvilinear relation, 曲线关系
1 S7 M" S: ~ ?9 _- c: T; N8 `Cut-and-try method, 尝试法
- _: R6 `6 @( h: N1 y |! P- z" UCycle, 周期9 h4 c! _; M4 P; l# A3 F5 X4 |9 O. p
Cyclist, 周期性8 f) \2 H+ \- Z
D test, D检验2 L8 N# {9 ]- p) [6 B
Data acquisition, 资料收集
8 i# ^8 m H: T7 c1 W$ R. W5 RData bank, 数据库) o+ t3 M4 o' {% B6 H. U; ]/ v3 J
Data capacity, 数据容量. H) I: r/ D* R6 K( j5 G$ C7 |" f
Data deficiencies, 数据缺乏( O( W$ M6 g* V" L" O0 |# [7 c; T
Data handling, 数据处理" `1 [% }4 w) ^8 b4 |6 `: l2 }
Data manipulation, 数据处理8 v) {, ^* P: _2 l0 |( b9 x
Data processing, 数据处理% u$ Q4 F4 z, r3 o
Data reduction, 数据缩减- t/ J, ~. @! k- C9 I
Data set, 数据集
6 q4 O6 M' _. L2 s" q1 eData sources, 数据来源
6 P/ X r7 @3 B5 R1 U$ n% l0 HData transformation, 数据变换
* g5 a- U+ g0 S% P% c- `2 F) T1 BData validity, 数据有效性& H4 U- W' g- U% O, j: o
Data-in, 数据输入
$ X" Y8 d! l; `; R$ MData-out, 数据输出
: `- s, t( K# G, oDead time, 停滞期6 T0 c4 Y# E7 Q, D1 r, U4 j+ o% X
Degree of freedom, 自由度
7 v& V0 B6 C$ s jDegree of precision, 精密度/ G6 Y2 {8 | I7 ^7 H
Degree of reliability, 可靠性程度* n. Z) u0 g% q, U, T
Degression, 递减
& G0 W) I, M+ x' h2 e; ?9 g+ \Density function, 密度函数) \6 E; ]& |, {% I9 y8 l' w9 P
Density of data points, 数据点的密度/ N3 g7 f. K b
Dependent variable, 应变量/依变量/因变量
" u& R ?3 M& ^8 s, I1 E. ~6 B6 ?Dependent variable, 因变量1 f) i; r8 O8 I, K6 N
Depth, 深度
9 x% D: k, N/ j+ g% y; z! E8 qDerivative matrix, 导数矩阵' p# g% o, \6 j
Derivative-free methods, 无导数方法( h/ A) }1 I- y* X" Z, `+ J
Design, 设计
! k5 }. R6 r; H7 i9 oDeterminacy, 确定性8 N0 I* c, O& j4 b. }
Determinant, 行列式
6 d+ y8 d0 C2 C. | W. SDeterminant, 决定因素
" S& E9 z1 m8 Y* _5 ADeviation, 离差
: D! o2 q; I. s9 j% e, NDeviation from average, 离均差
: j* N& A8 X8 m( N d- rDiagnostic plot, 诊断图. X4 W" j/ S2 k+ q2 X
Dichotomous variable, 二分变量# f9 A- m- P6 X
Differential equation, 微分方程% W, y- R+ U$ l
Direct standardization, 直接标准化法5 }4 {" E( ?, O+ z) S: E
Discrete variable, 离散型变量
; z; k+ l; u. q" B; u9 w) eDISCRIMINANT, 判断
/ ^4 h! R: l# Q" H# k7 yDiscriminant analysis, 判别分析9 u) i! [* y$ R! e& ]
Discriminant coefficient, 判别系数
4 I, @8 Z8 l f0 T' ^Discriminant function, 判别值
& `" p* e* g: \, n) S% EDispersion, 散布/分散度# g/ s& L, f9 v
Disproportional, 不成比例的
0 H( K6 ~7 R# vDisproportionate sub-class numbers, 不成比例次级组含量
/ H: Q9 G# j* MDistribution free, 分布无关性/免分布
2 [; T! G' ]- ^: X4 O5 cDistribution shape, 分布形状
- B7 ]9 T% I3 [1 z+ P1 xDistribution-free method, 任意分布法1 O; u* P) Y9 v! ~ m0 ?7 }% E
Distributive laws, 分配律; Q6 |& T( g% U& S2 V, X5 {
Disturbance, 随机扰动项
' ~. j- a D3 vDose response curve, 剂量反应曲线
4 [5 w) @$ E" D8 S0 P: A+ nDouble blind method, 双盲法
% b6 S; p1 `! w: `1 nDouble blind trial, 双盲试验
% R8 E& o' k7 d; ^8 G/ ADouble exponential distribution, 双指数分布% R0 l& S) D: M, _
Double logarithmic, 双对数
6 w7 f7 C$ h, p& `% oDownward rank, 降秩
|7 J6 B! t& {, _: gDual-space plot, 对偶空间图; Z3 D7 M1 S8 s+ i
DUD, 无导数方法% k( A8 g: p; i8 F6 s
Duncan's new multiple range method, 新复极差法/Duncan新法
9 i/ K# T3 u& GEffect, 实验效应& {+ R* }1 e2 H5 Z
Eigenvalue, 特征值4 P3 M/ ^6 f" p/ {4 r, D, V @
Eigenvector, 特征向量
# y2 t0 i& n4 W, j" V' A% rEllipse, 椭圆% b% W3 I; M: u0 L3 D! ^
Empirical distribution, 经验分布
) P, K8 r7 l* ~) V P# DEmpirical probability, 经验概率单位0 U/ H4 A1 l7 T8 \8 ?
Enumeration data, 计数资料 l$ |- x. W3 l$ K( T8 `9 i) T
Equal sun-class number, 相等次级组含量) A8 _, W7 a# n0 A5 Q7 ^# x
Equally likely, 等可能* {5 n( [8 S4 h: `- H, S
Equivariance, 同变性9 |; ^1 _" }# e9 R, `
Error, 误差/错误0 j7 ~" K* V- n, M+ u
Error of estimate, 估计误差
9 b+ I+ k; ~1 S1 D6 Q; ~Error type I, 第一类错误
% `5 B( G h/ h# h6 `Error type II, 第二类错误; x/ G6 B, ^( f: V& T
Estimand, 被估量
; E1 e7 C4 @' ?5 @5 ^) g# r6 MEstimated error mean squares, 估计误差均方; H. k. }$ ?4 E' u
Estimated error sum of squares, 估计误差平方和( M5 N+ X, F: f2 {' R' {$ Z! ~
Euclidean distance, 欧式距离, k3 A. ~2 o5 j4 f: r2 l8 r. u7 s- {# s
Event, 事件4 v1 g- x+ ~4 V
Event, 事件
3 I; L$ I6 F& H' k9 }Exceptional data point, 异常数据点
0 g9 z1 n7 U) f5 ]! }# yExpectation plane, 期望平面
. G- m5 c% ^8 }! N/ L6 [Expectation surface, 期望曲面
( F: j' k9 ]! C, [* e* l' `& FExpected values, 期望值8 G) e4 x( C" Y9 w" |3 K+ o2 u
Experiment, 实验4 [2 {) X5 G1 W: D$ T0 t+ U# ]
Experimental sampling, 试验抽样
4 a$ s/ [2 } @- U" K wExperimental unit, 试验单位5 n/ ]6 G( \ B& B. [! A
Explanatory variable, 说明变量1 f! w% a8 K8 p& W
Exploratory data analysis, 探索性数据分析/ e% Z. s2 P0 C# ~
Explore Summarize, 探索-摘要
. m. ], D b mExponential curve, 指数曲线" _ n* F: e b, W& U; @" V
Exponential growth, 指数式增长- V" o- d+ E" y+ L
EXSMOOTH, 指数平滑方法
3 m- T- A* k0 m" W' B" a! dExtended fit, 扩充拟合; X1 L; g1 \ Q6 ]
Extra parameter, 附加参数
1 w5 f! o" f4 @8 h' h6 N" fExtrapolation, 外推法. e* Q h" e% d# d2 i& T! E
Extreme observation, 末端观测值0 e' f5 Q. V" G& G
Extremes, 极端值/极值, g5 @8 q% C- d3 x) ~
F distribution, F分布 f+ _: A& L* u- ?- I5 a' {9 c
F test, F检验7 n/ j7 I& b" Q* O* ?
Factor, 因素/因子' v' [6 u( f( r
Factor analysis, 因子分析5 S( d+ G# h' ?: F/ [( H; B
Factor Analysis, 因子分析) p1 {1 x/ H& Y* P6 v; m) a
Factor score, 因子得分 9 K$ a# h0 }0 @9 i% z7 k6 C' t. y k
Factorial, 阶乘
2 W/ m: H5 V' ]/ G% k+ C( r9 D KFactorial design, 析因试验设计
) V/ x9 d2 |' C# E, e: r. AFalse negative, 假阴性
) U2 f4 P8 H. [3 qFalse negative error, 假阴性错误
% V% z6 P. q& `; E- M. D; v) QFamily of distributions, 分布族1 ?& g1 U& j, x3 j; `: A
Family of estimators, 估计量族
+ N* g1 Y2 w; X- u4 BFanning, 扇面
, t6 o2 {8 d0 m5 CFatality rate, 病死率
5 F. E1 t% A w4 M0 dField investigation, 现场调查0 P% f2 j& c& q! W2 [2 `+ S* p
Field survey, 现场调查
0 J( j/ Q+ r1 N2 q5 r: [( EFinite population, 有限总体
3 U, h% _- x& P' A$ r2 z OFinite-sample, 有限样本* m/ n( `5 J5 Q7 L
First derivative, 一阶导数
; a" a1 o3 P4 I: }+ [2 I4 f3 P. QFirst principal component, 第一主成分
: ?* }* X! `+ N) R3 b8 z/ {/ NFirst quartile, 第一四分位数
6 }$ g, G8 Z6 d& yFisher information, 费雪信息量! f- i3 L" {. ]% p
Fitted value, 拟合值3 o7 U. R3 V f% w P, T
Fitting a curve, 曲线拟合. k, e7 N4 p# u. ?7 E, B& `
Fixed base, 定基
2 }% T1 l8 i! ~+ w; b# ^Fluctuation, 随机起伏/ A+ K: f, K1 d
Forecast, 预测
% M8 m9 A' P5 B1 V: H- T4 N4 lFour fold table, 四格表
9 t4 b3 i$ Y8 y7 R3 E, p$ }" c- l7 ?# VFourth, 四分点
) j" { u9 N L7 C/ S: _6 `Fraction blow, 左侧比率
4 Q. G. H2 z( A* i# y5 O( d4 E; jFractional error, 相对误差
0 c& p4 o( x7 u! _) _3 MFrequency, 频率. c" z) q' L" P3 [ a( b$ J1 B) V! H
Frequency polygon, 频数多边图
. p/ ~( ~; L) K0 wFrontier point, 界限点# k e' X4 ^4 Q- n W) f
Function relationship, 泛函关系; `3 Z. ~6 ?% A; A- |
Gamma distribution, 伽玛分布" |/ O: h/ e+ \ S) l# [
Gauss increment, 高斯增量
4 |0 c0 P1 K) w1 O [6 F1 w# n( V$ bGaussian distribution, 高斯分布/正态分布
' S. _: q4 D, m; C0 cGauss-Newton increment, 高斯-牛顿增量
- i+ y$ z, L |/ LGeneral census, 全面普查
# B" u* Y7 @0 Z7 f U" Q/ xGENLOG (Generalized liner models), 广义线性模型 % O! s3 W' Z1 S4 {$ v' X" G- z$ E
Geometric mean, 几何平均数
3 j4 G) }. c) O0 l) C% ]1 yGini's mean difference, 基尼均差
' g2 J9 {2 U1 R% p! ?GLM (General liner models), 一般线性模型 , x- D& i( e' b" B/ O
Goodness of fit, 拟和优度/配合度
: u _7 H4 e* n/ HGradient of determinant, 行列式的梯度, P; k$ I4 w9 t
Graeco-Latin square, 希腊拉丁方, x) \" z y6 R6 N$ H' b& ?( x
Grand mean, 总均值( E9 e( o/ z1 W; h2 v
Gross errors, 重大错误$ U* W* p' S, G; f
Gross-error sensitivity, 大错敏感度
/ t& O1 O2 U- t) A7 QGroup averages, 分组平均
9 L; Q/ L O" p! f0 ~( @& KGrouped data, 分组资料
9 R, t z; X" ]; ?6 o7 k. g9 fGuessed mean, 假定平均数! b7 l5 `% D4 A% L0 i2 h
Half-life, 半衰期/ z$ S( `8 \" D$ h0 z+ c9 Y
Hampel M-estimators, 汉佩尔M估计量+ |' W: M3 U5 ~7 W; a. q- @
Happenstance, 偶然事件
: W% d- h# q0 WHarmonic mean, 调和均数 ^) r% g% _. F1 s, Q ~
Hazard function, 风险均数
$ r2 s: _7 Z# S9 O' @! cHazard rate, 风险率
+ }. R' P7 }3 m( r- a# X- aHeading, 标目 1 L: k5 h2 ]" Z& w) y0 S" s
Heavy-tailed distribution, 重尾分布1 g$ f# `: \, B/ [- Z
Hessian array, 海森立体阵
6 i6 j0 k" Z: {4 E5 r* _6 y, wHeterogeneity, 不同质
1 Q! T; p1 s- {$ v: ZHeterogeneity of variance, 方差不齐
2 H; p4 m1 U. c9 n& {Hierarchical classification, 组内分组! z# Z* T; S8 I7 i. Z1 H ?
Hierarchical clustering method, 系统聚类法
2 |0 O" c0 d" hHigh-leverage point, 高杠杆率点% L. @ I% r! S' I
HILOGLINEAR, 多维列联表的层次对数线性模型
* r2 L5 W: x( M, a' ?# t( O0 `( bHinge, 折叶点
+ w( s7 B4 j; A. `Histogram, 直方图
2 ~6 Q) Q' h* w- W5 o4 T/ JHistorical cohort study, 历史性队列研究
8 X+ \. ]$ k7 Y: D0 c5 C5 ?* c% vHoles, 空洞+ R& H0 P! W1 K- ?
HOMALS, 多重响应分析+ d1 X; c6 b% y, o
Homogeneity of variance, 方差齐性# B6 u" w) B( v) s+ t7 |( x. _
Homogeneity test, 齐性检验1 I8 y' x$ c, V( q7 U% U
Huber M-estimators, 休伯M估计量* d9 j0 M1 M4 q
Hyperbola, 双曲线
, f! P+ U0 f8 |2 B& t; N/ L2 X# zHypothesis testing, 假设检验+ l1 ?* v) Z$ [- r% @. a9 e* ]$ b
Hypothetical universe, 假设总体
0 n) t+ K- V! c- v( X( qImpossible event, 不可能事件
, f0 g5 o) a/ t- m# r- rIndependence, 独立性7 Q- h# y. @1 g" R
Independent variable, 自变量
1 L3 N6 q1 s; k4 r' |9 B& X; ~Index, 指标/指数% n7 `+ e9 b' [3 B- O a
Indirect standardization, 间接标准化法5 J6 Q" R0 }) B. @ R5 X
Individual, 个体
; p, D5 w5 T9 m! ?: hInference band, 推断带4 Y: J! }- @. K J: ~6 g
Infinite population, 无限总体
* i4 Q8 Z. j, ^2 Y+ iInfinitely great, 无穷大
# w: I5 n, K2 T Y' Q2 |: g2 ~" BInfinitely small, 无穷小9 u+ j4 |' _ K# E6 Q
Influence curve, 影响曲线
( N. s+ k$ x/ OInformation capacity, 信息容量' b# K/ `0 p% D2 U' w
Initial condition, 初始条件% b, J0 M% F ~: n! i% {
Initial estimate, 初始估计值( a4 _: {; Z" _: f0 G
Initial level, 最初水平
" P" S) O' |4 c" |Interaction, 交互作用; S: U [; u0 P
Interaction terms, 交互作用项8 A3 Z2 Y6 G% O- a
Intercept, 截距
( H, `$ N3 Z7 Y6 GInterpolation, 内插法0 x, |" r' a1 o5 B2 i$ V6 t* h
Interquartile range, 四分位距9 L& c- w; y/ U! m+ m6 T
Interval estimation, 区间估计
# K) ?: C% R* b( z: CIntervals of equal probability, 等概率区间; n, d( r+ d/ Y7 J/ w. A
Intrinsic curvature, 固有曲率5 Q: |4 L2 `3 {7 o! \& y2 B9 U+ U
Invariance, 不变性+ @' D f, E3 e( t
Inverse matrix, 逆矩阵3 p# g. _5 u$ u! N
Inverse probability, 逆概率% O/ X% ~, W/ h7 R
Inverse sine transformation, 反正弦变换. ~% r% Y% r/ G* ?
Iteration, 迭代
3 h: y3 y Z: m* N0 jJacobian determinant, 雅可比行列式; Y" r ]7 v" f: T$ h
Joint distribution function, 分布函数+ v1 `4 w2 |6 O3 K% D3 c
Joint probability, 联合概率
6 b+ `, i" Z, s4 @7 H2 i, v8 nJoint probability distribution, 联合概率分布6 z5 b6 e9 M6 L$ Z* q+ s& E# I
K means method, 逐步聚类法
# k( U4 W; I, f" _3 bKaplan-Meier, 评估事件的时间长度
! `3 }% s& \7 J6 sKaplan-Merier chart, Kaplan-Merier图- l" i! U( {! a) o
Kendall's rank correlation, Kendall等级相关+ [8 G& y& r& }8 |: e" D4 \
Kinetic, 动力学
8 y, g- K5 W' V, \3 z! C, eKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
5 m1 s) b3 K5 C# x) x3 ^3 i$ _Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
. g1 ?6 T; H$ B( }+ [( W6 I5 f) {Kurtosis, 峰度
; m# | L, H* V8 z; TLack of fit, 失拟
% c5 ^3 [4 j7 V! iLadder of powers, 幂阶梯9 V2 m8 O) z4 K g# k2 C# |- {
Lag, 滞后6 A; H" g9 _1 t7 [- W) z5 x8 ~# F; T
Large sample, 大样本
: I% u% @6 `% N* k; f9 F: GLarge sample test, 大样本检验5 }# k: F$ @7 Q% ~* c( S: z
Latin square, 拉丁方8 h; v. U" d* b$ ~: |5 E
Latin square design, 拉丁方设计
# I! J3 F) B# v: M6 e O5 b/ ]Leakage, 泄漏1 S/ d; G' N+ F7 m T# z4 e
Least favorable configuration, 最不利构形
3 Q- S `$ _% N) |# O. L; zLeast favorable distribution, 最不利分布
; i7 F8 Y% x, j5 WLeast significant difference, 最小显著差法 M2 @! m, i8 {4 E! P
Least square method, 最小二乘法
( j& V& F1 T7 f8 N8 [ N6 V' o, mLeast-absolute-residuals estimates, 最小绝对残差估计8 S0 x8 E' t# k. w3 x& f/ d2 y" q* M
Least-absolute-residuals fit, 最小绝对残差拟合
4 E; H2 N; J8 W& Y( YLeast-absolute-residuals line, 最小绝对残差线, R) a+ a7 n% n8 p
Legend, 图例5 z; B( i% z& n1 C, p
L-estimator, L估计量
7 i3 |7 o2 p8 NL-estimator of location, 位置L估计量; @3 y8 g9 [( R8 a) \
L-estimator of scale, 尺度L估计量7 M# z2 V) ?, o( V
Level, 水平
+ d9 v% i4 b( W2 y/ } FLife expectance, 预期期望寿命4 z! `/ {+ x- C4 {3 ]$ V
Life table, 寿命表
1 I! X3 X5 r, z5 i0 e; @Life table method, 生命表法
! Q0 e. O7 a% X9 z0 G4 {( g# ]* g0 XLight-tailed distribution, 轻尾分布
! ~0 |3 D6 H0 c& G2 A0 k$ VLikelihood function, 似然函数
7 w* p! K0 k* L5 \) P3 W* t# @Likelihood ratio, 似然比6 e8 w9 y8 F, G* R( Q8 i
line graph, 线图! P2 @( q/ u8 ^
Linear correlation, 直线相关/ C4 W0 Z, P& U# e% K8 L9 ]
Linear equation, 线性方程
r& M$ P" p- s) I5 ]" Z$ C [ E' HLinear programming, 线性规划
+ i' X0 @- l8 U7 H" ULinear regression, 直线回归
- w4 u2 {% r9 c iLinear Regression, 线性回归7 ]( [/ p* F4 \2 R! C: w4 f
Linear trend, 线性趋势3 \9 e5 ^( _2 f8 c
Loading, 载荷
3 B! z6 q' ]$ F6 ]5 z, KLocation and scale equivariance, 位置尺度同变性& l& d: l! C! C/ G. b
Location equivariance, 位置同变性
1 l2 N+ R" w! D+ B" H7 z) VLocation invariance, 位置不变性
9 M8 A9 p; ] a) d9 rLocation scale family, 位置尺度族
/ z0 e1 u9 F# G- i6 YLog rank test, 时序检验
, \2 B4 f p2 C2 Z# XLogarithmic curve, 对数曲线
2 m9 Q/ W$ o& `+ iLogarithmic normal distribution, 对数正态分布
% c% F, i( s) l7 X+ b+ X2 nLogarithmic scale, 对数尺度
1 T) A S, @ \, V; eLogarithmic transformation, 对数变换
. J3 F/ k0 i( U7 V! c0 e. q" pLogic check, 逻辑检查
+ y1 \' T0 t) mLogistic distribution, 逻辑斯特分布
2 @& H' p. A8 h$ D9 e9 A4 nLogit transformation, Logit转换
6 ]2 g- F/ w2 \, M2 U6 cLOGLINEAR, 多维列联表通用模型
& u- g3 g9 F$ jLognormal distribution, 对数正态分布
8 r! _- Q7 \- f0 m) I/ _8 ALost function, 损失函数
! L2 W' f) {6 M" n5 c2 F6 B4 PLow correlation, 低度相关, J6 N8 I4 `7 [& J3 i
Lower limit, 下限
9 Y7 s N( M% b" B' Q& ^Lowest-attained variance, 最小可达方差2 e4 d: n4 J( j( x+ c% v7 X
LSD, 最小显著差法的简称( |3 d# R8 N; H( ~
Lurking variable, 潜在变量
! ]& ~; A) z1 s ZMain effect, 主效应 Z) T1 H! E; m3 d% X1 v. ]
Major heading, 主辞标目
8 L8 f( }* j7 J8 z; R2 Z/ n* OMarginal density function, 边缘密度函数4 ^/ }- j, d2 S4 P0 k3 U
Marginal probability, 边缘概率
' U! d6 r+ L- H8 yMarginal probability distribution, 边缘概率分布
' h: Z, w: D! e. PMatched data, 配对资料9 r* _" y9 G; ]% I* O
Matched distribution, 匹配过分布
. A* M1 s G6 M xMatching of distribution, 分布的匹配: L( e% B9 h$ [' A5 U# O7 m
Matching of transformation, 变换的匹配
2 l: O' w+ X3 @# x3 _8 w/ ^% O" }Mathematical expectation, 数学期望
7 P3 v0 [" A) r4 `% ?0 Y$ C$ IMathematical model, 数学模型$ a$ I& ?; w7 m6 {! c% O* a
Maximum L-estimator, 极大极小L 估计量' U2 r0 b% d- G
Maximum likelihood method, 最大似然法
! b( N# i0 c% f4 ?' I# \9 O4 ?, wMean, 均数
: W5 c, O/ ]2 V( XMean squares between groups, 组间均方, v" y" w# a+ ]* p0 }+ e
Mean squares within group, 组内均方; V) M! k( @/ ^5 J. _
Means (Compare means), 均值-均值比较* n) o4 f4 {/ z1 B9 |% Y' w
Median, 中位数
. [ }6 ~; I# d( h! wMedian effective dose, 半数效量3 `0 L$ B) {% j9 `1 X
Median lethal dose, 半数致死量6 E5 x+ s# g1 x, b- h0 Q
Median polish, 中位数平滑7 D& I' b2 J% l$ ~) F$ a$ R
Median test, 中位数检验
! i w2 T S/ z# a- B wMinimal sufficient statistic, 最小充分统计量. E5 Z7 {% R5 [$ P5 b
Minimum distance estimation, 最小距离估计
6 ~ N2 B- O6 Z7 g( x* WMinimum effective dose, 最小有效量
4 ]5 E; O g. A" LMinimum lethal dose, 最小致死量
) ?- X$ R- z5 E$ lMinimum variance estimator, 最小方差估计量/ |5 L( }7 f. a2 H3 h F( ]
MINITAB, 统计软件包1 Z; c" W" \6 A* T: a0 |
Minor heading, 宾词标目
- I" U* k# }3 B) ~6 B, X/ n' C/ m& m# G* wMissing data, 缺失值
% M& s& [- w# _' M" M, ~3 w; [5 GModel specification, 模型的确定3 G: P6 n1 j1 r T& T5 I( n9 c
Modeling Statistics , 模型统计4 [3 j1 S; Z& t9 V, [& n! f2 Y
Models for outliers, 离群值模型
( M/ g g! l+ {! _: rModifying the model, 模型的修正
; d4 a9 T, T) c" L- h- ?Modulus of continuity, 连续性模. P6 v8 _$ p2 ]' e5 f L$ ]
Morbidity, 发病率 + I( q0 p9 e! f5 T5 G
Most favorable configuration, 最有利构形: t" D# G8 u- n1 T4 K, i
Multidimensional Scaling (ASCAL), 多维尺度/多维标度+ h- ^$ C& ~' p6 b
Multinomial Logistic Regression , 多项逻辑斯蒂回归
6 s% \6 a" S! u# g0 u: wMultiple comparison, 多重比较( ]2 o3 M# d. @+ G
Multiple correlation , 复相关4 ?4 c# x) h- p, t J; }3 l2 ~6 G
Multiple covariance, 多元协方差
* a# m1 T" X% @$ }% F0 \2 h4 qMultiple linear regression, 多元线性回归
5 E, G& C5 W2 t- gMultiple response , 多重选项
9 [' [0 Q) W3 a1 f- \ s9 IMultiple solutions, 多解8 E7 ]$ R7 o% H8 H% y/ V$ ^" Y- y
Multiplication theorem, 乘法定理( ^2 K8 u9 W( J I) |
Multiresponse, 多元响应
d; J# |0 Q$ _5 m) cMulti-stage sampling, 多阶段抽样4 f* Y, o1 r: E; c
Multivariate T distribution, 多元T分布
9 {& B) d$ d+ C0 d' y2 {Mutual exclusive, 互不相容
/ f' J2 W$ h1 O+ A3 x- kMutual independence, 互相独立: e6 y5 l5 q. r3 [! N
Natural boundary, 自然边界
+ m$ {. o. V" S* Z6 K4 H' j' k- eNatural dead, 自然死亡+ g; T' ~$ G2 K; Y
Natural zero, 自然零1 R: E @1 g7 ?( ?( T
Negative correlation, 负相关; l8 l8 p3 O. D* }# q5 v
Negative linear correlation, 负线性相关, R: i" D# \( o
Negatively skewed, 负偏* G9 w' }2 t r) f3 ^* j T( l
Newman-Keuls method, q检验+ j) q3 r: h. F0 \" D9 k* x' U
NK method, q检验/ ~' U% R/ n. n6 q
No statistical significance, 无统计意义" n2 r# [( R5 H& C+ b
Nominal variable, 名义变量! K0 {4 t6 X1 S6 H% F
Nonconstancy of variability, 变异的非定常性
" R* w$ ~6 P9 q# o ^Nonlinear regression, 非线性相关* v9 K7 e4 `$ T6 y8 g! M* t. C
Nonparametric statistics, 非参数统计
, [2 ?* u g) p( O+ P$ L0 DNonparametric test, 非参数检验6 ^; G9 }+ x, j m& z
Nonparametric tests, 非参数检验
/ `+ x$ u; r3 b8 |8 k) j3 [Normal deviate, 正态离差5 U) E9 ^+ C, P5 S
Normal distribution, 正态分布
0 J* a3 o& F. ]4 _Normal equation, 正规方程组
) s; i* G' n, g5 j% O' |! dNormal ranges, 正常范围* c8 t5 s4 X. t
Normal value, 正常值, d: s* o. D) s2 w
Nuisance parameter, 多余参数/讨厌参数% t0 B2 O) Q1 \2 @! P
Null hypothesis, 无效假设
2 h8 [: `* ^ I( [+ x2 g! E& A/ ~Numerical variable, 数值变量! @- \- m2 B8 j4 |, H _% V$ r
Objective function, 目标函数5 Y: }; X/ a& f; k3 F+ c
Observation unit, 观察单位3 K% x; o4 E, P' j% m9 G
Observed value, 观察值# d& j! j* w/ T9 K' e6 V0 r" K
One sided test, 单侧检验
' j& p6 n/ f' B0 ^8 v3 xOne-way analysis of variance, 单因素方差分析- C+ Z' d: A5 M) b7 i
Oneway ANOVA , 单因素方差分析
2 n* \" K' {( \Open sequential trial, 开放型序贯设计
; E9 B# w' l& u( d7 h/ XOptrim, 优切尾
5 _( Y* h9 h# }9 `9 ZOptrim efficiency, 优切尾效率' ~ z% g' e& B5 ]
Order statistics, 顺序统计量
/ Y- l3 x/ b" l: UOrdered categories, 有序分类
( F% c/ c9 V2 Y# m- `/ |9 y5 aOrdinal logistic regression , 序数逻辑斯蒂回归
. {* ]% }; b4 ? A" |& f2 `- eOrdinal variable, 有序变量+ s/ ^5 X, I: C; O- @
Orthogonal basis, 正交基
5 F: h) ?" m; b6 Y1 r- iOrthogonal design, 正交试验设计- J) s, l8 l H) O! f) c
Orthogonality conditions, 正交条件4 K# S. k/ @8 s
ORTHOPLAN, 正交设计 # o: [/ E! ? Q- V
Outlier cutoffs, 离群值截断点
% }2 Y4 X# I: Z2 FOutliers, 极端值, L. w5 g8 ]$ x6 n
OVERALS , 多组变量的非线性正规相关 4 S4 r9 q- e8 {$ S! d* ~
Overshoot, 迭代过度, [' I: V2 D! z3 A8 L: \
Paired design, 配对设计
( Z. y& g- T" H$ I( p% lPaired sample, 配对样本8 e: ~( f& T& @
Pairwise slopes, 成对斜率+ F1 r6 }& T0 X; s
Parabola, 抛物线
0 w4 N5 \: T8 |5 u; \+ p3 k6 sParallel tests, 平行试验
; U1 ^: J, u, k& P2 H/ J) hParameter, 参数
3 w# q# a0 B( P) `( ?3 E9 Q$ H) ?Parametric statistics, 参数统计- _9 }7 C, O& \ D0 m6 j, h
Parametric test, 参数检验5 p- `! \* ^) G$ O) {# M1 A
Partial correlation, 偏相关8 L0 R9 k' Q, m3 z+ x; ^
Partial regression, 偏回归
' Z* f9 z% C* A% |' n2 ZPartial sorting, 偏排序
2 g" z8 o9 V6 j1 @3 c4 ^+ N9 \Partials residuals, 偏残差5 S+ U' G4 H, z2 a9 z
Pattern, 模式: M. @1 [ g @6 {7 }- K
Pearson curves, 皮尔逊曲线
0 _# q# L, a$ u! U; s5 }Peeling, 退层* v! d; ~3 @' H+ S u5 T( q
Percent bar graph, 百分条形图- F5 f9 z' U/ `. y
Percentage, 百分比2 _6 N' R/ O1 ^
Percentile, 百分位数
- j/ t% l. K/ ~, S) u6 WPercentile curves, 百分位曲线- X) Z a) {& w1 C) i. d) [
Periodicity, 周期性5 s* ~8 ]2 l/ X: Y( j2 E" T0 S
Permutation, 排列/ D. t( I# l! U
P-estimator, P估计量
7 M. d7 _- e0 DPie graph, 饼图1 l1 ^; q6 C9 i9 u4 v5 ~6 h
Pitman estimator, 皮特曼估计量! n1 W& T/ J. V6 Y5 L
Pivot, 枢轴量
# a; N2 ^# \, X; iPlanar, 平坦
* c& U9 f; M: z/ \3 uPlanar assumption, 平面的假设
) L, a Y1 ]2 v# A) g% \PLANCARDS, 生成试验的计划卡/ F' H; R. x. r$ Y7 N: x
Point estimation, 点估计6 E& [' c. Q% Q, T# o5 J
Poisson distribution, 泊松分布
0 T/ v, w/ z0 a) t% ^Polishing, 平滑
' E- h" o% U' Y" _+ c+ M BPolled standard deviation, 合并标准差
* i$ M$ P* N/ h9 KPolled variance, 合并方差
2 Y* w5 j- @/ {8 Y7 B/ uPolygon, 多边图
9 B# H4 v( W! t* a- KPolynomial, 多项式' ?- W( I' M8 S
Polynomial curve, 多项式曲线- x3 Q* \( l$ S- s# T+ q7 p$ s+ r
Population, 总体. [! N- H+ w) t# P
Population attributable risk, 人群归因危险度
, Q# g4 ]; l( z" K$ I$ _Positive correlation, 正相关
4 {1 Q1 I4 e# R: J2 k- q# H$ G+ _Positively skewed, 正偏& v8 I: f) R3 _$ W# o* a
Posterior distribution, 后验分布/ O: Z b( a4 G3 z0 @3 ?
Power of a test, 检验效能
. Q8 w$ x0 L: d, s" I9 vPrecision, 精密度
* ?/ D; V. l5 T3 \* kPredicted value, 预测值
9 l. T+ ~3 q" V0 g* ?. t7 y5 ZPreliminary analysis, 预备性分析
( Z7 U4 Y9 p5 f, `; y3 RPrincipal component analysis, 主成分分析: W6 _* q8 \" ?6 C0 H
Prior distribution, 先验分布
4 m+ [( W* _; ?! O) {Prior probability, 先验概率
" {7 ~8 v" @/ B- E; s, b! W AProbabilistic model, 概率模型6 ~1 k! F, V8 Q: x8 ~4 k6 M) l
probability, 概率
1 V& d' a, r$ J+ ?1 C' \. gProbability density, 概率密度3 y3 A6 x" B* L7 ]6 A
Product moment, 乘积矩/协方差
/ c3 U3 {/ j/ [7 j3 E, K7 M& TProfile trace, 截面迹图
# A( f# w/ h# T4 oProportion, 比/构成比, b# R. g2 z! W `1 R H8 Y* C
Proportion allocation in stratified random sampling, 按比例分层随机抽样
( K+ J+ z5 k# `, M- A; p, cProportionate, 成比例
4 Z$ ~- ?, u/ W& W2 w, u! {Proportionate sub-class numbers, 成比例次级组含量6 d- ?4 y/ { W+ [4 k$ F
Prospective study, 前瞻性调查
/ ~: `: `3 z4 S J( RProximities, 亲近性 1 b# c- H o! m
Pseudo F test, 近似F检验
4 i7 A9 z. o4 @. p( S$ e( ePseudo model, 近似模型5 Y% p5 o9 |& [
Pseudosigma, 伪标准差3 h. r9 P# S6 s, F6 ]9 N( z
Purposive sampling, 有目的抽样
2 V x' r4 h+ HQR decomposition, QR分解
. N; @0 Z2 k% I2 ZQuadratic approximation, 二次近似
" p9 I0 }; ~0 E3 L9 ]& l7 g+ jQualitative classification, 属性分类
5 j# r O I9 o# p) a. S6 [Qualitative method, 定性方法
: l8 U7 y6 X4 m; l, CQuantile-quantile plot, 分位数-分位数图/Q-Q图# r& T" J; p- [5 y
Quantitative analysis, 定量分析8 w d, {% K) ~* ~; m& ?
Quartile, 四分位数
2 {$ }4 k' e- R% S( }& Y; d) ?Quick Cluster, 快速聚类
, z; e& O: ?" g: q/ p7 ]Radix sort, 基数排序6 Z. V2 {7 h0 z4 t" r- c6 @4 q+ m, p/ o
Random allocation, 随机化分组4 Z9 k! u2 k% D
Random blocks design, 随机区组设计
; B( E( k; ^/ B5 ~' w, qRandom event, 随机事件3 n6 X$ [* K2 l% \0 |" @( Z+ o
Randomization, 随机化& D& j6 f m. ~ a
Range, 极差/全距
" j5 g6 O2 X+ r9 t* }- C7 }Rank correlation, 等级相关& S) G" `% P. k$ @
Rank sum test, 秩和检验
. W; c( }" {! O; H: FRank test, 秩检验 [3 h& I- A3 M8 H- {& o& {
Ranked data, 等级资料+ X. j/ h0 N% p' X" u: e
Rate, 比率
/ A4 S0 U$ ^0 ~3 N& M* ~# a% zRatio, 比例3 t; f0 B7 o& Z g. y' R
Raw data, 原始资料6 w2 W) g, F, R; m+ z# X9 ^ U
Raw residual, 原始残差2 I, j$ m- e5 ?# I; _6 T B
Rayleigh's test, 雷氏检验
* @# [9 Y% d, E1 g8 X% w& SRayleigh's Z, 雷氏Z值 ; I4 {3 b, Q( u1 K
Reciprocal, 倒数( E. m8 E0 d7 F9 N
Reciprocal transformation, 倒数变换# m5 L, g" o6 n2 `* f
Recording, 记录
# w: l1 E, N5 o% f" MRedescending estimators, 回降估计量& S* r% b" W( E+ b0 f7 r, N
Reducing dimensions, 降维
" h4 @ ]; X6 ~- P i/ yRe-expression, 重新表达3 ?5 S2 s7 v9 ^/ L& u8 k- A( L
Reference set, 标准组
% q0 G" Y$ L& }/ ], ~/ p$ L4 bRegion of acceptance, 接受域3 _( w& ^) N( O% H0 A3 r
Regression coefficient, 回归系数+ w2 R) F$ ?; Y. s" W. S7 A
Regression sum of square, 回归平方和& ]2 B' @3 F# b& h4 A
Rejection point, 拒绝点+ u8 r, i$ K3 C+ ?( O5 M
Relative dispersion, 相对离散度
' J4 J* _& D9 P! i! G2 ~* }% uRelative number, 相对数% B) g; |1 I2 w
Reliability, 可靠性
9 y3 z7 p; d! J, EReparametrization, 重新设置参数
- `' F! [" L/ {7 N+ \* q" r! y3 eReplication, 重复
+ b8 T1 t" p3 d8 T* N& P* AReport Summaries, 报告摘要
# m) b% V; w. l5 d; j: uResidual sum of square, 剩余平方和0 a" E0 Q( u9 O9 {0 p6 i
Resistance, 耐抗性
1 ~7 \8 `% G- O/ S; RResistant line, 耐抗线
! u% Y: v, \- ?" J" `Resistant technique, 耐抗技术6 u8 h4 O) X3 q9 q
R-estimator of location, 位置R估计量6 I1 ]! V7 j, w z
R-estimator of scale, 尺度R估计量1 ~3 B- J A% S8 L6 I
Retrospective study, 回顾性调查5 U* K' S2 H! Q& C8 R$ @
Ridge trace, 岭迹$ O& E$ r8 p& W( `. u
Ridit analysis, Ridit分析
! a5 B& l9 _) b3 iRotation, 旋转
/ X4 @2 J: b5 u1 o3 i/ N" X# _2 {1 eRounding, 舍入/ Y3 {/ q4 b! w+ w' p
Row, 行# R, k: |2 c6 Q! e
Row effects, 行效应
, W! F5 {# k$ S7 s ?1 U; O; i0 k1 ~+ [Row factor, 行因素 w( m l8 k0 `0 _
RXC table, RXC表
4 Q6 v. x d' k( ISample, 样本$ K2 b8 |6 o6 d/ |
Sample regression coefficient, 样本回归系数9 T" [7 T* I% ?9 V4 C |
Sample size, 样本量
: A6 I# Z8 o9 f7 C4 R4 w/ U! BSample standard deviation, 样本标准差0 Y, P5 N+ R8 h* Z+ Z1 V' s
Sampling error, 抽样误差# z8 e; p& m& n# A. f
SAS(Statistical analysis system ), SAS统计软件包
$ ?( V! {0 E) y: g y7 EScale, 尺度/量表
8 N t" O2 |4 N. z8 x6 Q( TScatter diagram, 散点图
i3 o. B0 a0 i) d1 G8 z: `Schematic plot, 示意图/简图/ I$ l) B8 c4 F. {- U) Q/ q4 k
Score test, 计分检验
9 J0 K9 G* G& Y! r3 w$ W- }# QScreening, 筛检
" b8 d$ f6 |# W. P3 O) z( ?SEASON, 季节分析 M( l/ N7 U' f
Second derivative, 二阶导数* S; u1 M" N0 L F% ]$ x
Second principal component, 第二主成分
7 e) }2 o2 k9 p5 T& SSEM (Structural equation modeling), 结构化方程模型
# A0 `& `7 u; g [$ MSemi-logarithmic graph, 半对数图: n1 ]1 I: ~( }, v( \9 I
Semi-logarithmic paper, 半对数格纸
: }- O2 {4 l; V$ t- [1 @Sensitivity curve, 敏感度曲线
4 h+ ^ X% x; o) [& D/ uSequential analysis, 贯序分析
6 r0 X c8 V9 CSequential data set, 顺序数据集
1 F2 N, V3 K4 w9 ?Sequential design, 贯序设计+ L8 i% F1 f$ A+ ]& B* J
Sequential method, 贯序法; e# q2 j' p! T- d% P0 K( h
Sequential test, 贯序检验法
3 e! s# X- x/ S8 X4 i7 y( Y7 mSerial tests, 系列试验
/ N3 Y( [/ m4 b) B. A H& }4 S( ^3 aShort-cut method, 简捷法 ) n, n2 N) ?# j* W) a; [
Sigmoid curve, S形曲线
8 V# M8 B8 V3 S$ ZSign function, 正负号函数+ C; ^, V7 n( R9 w
Sign test, 符号检验6 X& b0 E, d6 H# A5 G
Signed rank, 符号秩
! f1 L9 `: T7 L" H$ ZSignificance test, 显著性检验7 O% `5 @. a, j4 v# H' c0 U
Significant figure, 有效数字) K: |* [ F2 `
Simple cluster sampling, 简单整群抽样7 t, M1 Y: O: B- g7 q. `8 |
Simple correlation, 简单相关4 k# W7 W6 A9 ~5 T9 u3 H
Simple random sampling, 简单随机抽样
7 s$ F) v" R2 i% N. n* cSimple regression, 简单回归
+ U! a% }9 o2 a7 Z1 _ H( l+ R R2 q' jsimple table, 简单表* W' n# H5 i) Q0 k0 r1 J
Sine estimator, 正弦估计量& N& C1 K1 C& B! y5 I
Single-valued estimate, 单值估计
# F2 w+ O3 ~ d0 e5 x1 fSingular matrix, 奇异矩阵
! E( D, }1 i/ j& Q5 \# dSkewed distribution, 偏斜分布) f" g8 E5 L; i: `
Skewness, 偏度9 d3 d& t& N- N9 ^7 ]" O8 Y4 v
Slash distribution, 斜线分布3 H& }5 Q/ P; j4 q- O+ [2 Q2 \8 [
Slope, 斜率9 e2 e- @7 C4 E$ {$ Y t5 u& g# a
Smirnov test, 斯米尔诺夫检验
7 o) d* j( H6 L7 {5 _' j9 ESource of variation, 变异来源
' u }8 j' G1 C }6 fSpearman rank correlation, 斯皮尔曼等级相关' u. B# ]9 t8 |1 g/ n
Specific factor, 特殊因子2 N! J) F! o2 d- ~
Specific factor variance, 特殊因子方差
! Y% u' \+ l+ x- N" N9 N, k6 b# e( kSpectra , 频谱0 `3 o# R/ O: D; @+ G, q! E" v
Spherical distribution, 球型正态分布
& R( I; e+ t* W: e Q6 _Spread, 展布8 l: `9 z& u9 b" }" ~9 {$ Q
SPSS(Statistical package for the social science), SPSS统计软件包/ x/ K' x- M8 ]- ^" @0 @
Spurious correlation, 假性相关
% u, L2 y; q6 t: ]. pSquare root transformation, 平方根变换' l. \5 H7 S9 a; K2 K6 L
Stabilizing variance, 稳定方差
: u' v. q( f2 B/ d aStandard deviation, 标准差* \0 p# Y, Z. h1 M. o$ }: l! \
Standard error, 标准误. }. _* ]/ @8 U( |; [1 L
Standard error of difference, 差别的标准误; e' N, \+ x& N9 {6 m% n
Standard error of estimate, 标准估计误差
3 j. I& Q6 ?( n1 MStandard error of rate, 率的标准误+ c- d3 |1 {4 k: `4 B
Standard normal distribution, 标准正态分布
2 Q) f6 i: w [& kStandardization, 标准化( i8 p$ o4 n7 y+ ^# O0 i) W
Starting value, 起始值* H/ L0 e2 a1 n
Statistic, 统计量3 }# V3 U, c C: S
Statistical control, 统计控制* T4 N) O- n! p2 z$ I+ f2 _
Statistical graph, 统计图$ s/ w3 `; q5 f1 l8 D* y0 o
Statistical inference, 统计推断3 H1 K/ a1 D* W8 i
Statistical table, 统计表/ u( V5 ~* K. ^# M l0 _1 v
Steepest descent, 最速下降法, [- k) o, V+ q/ Y8 T$ D
Stem and leaf display, 茎叶图 \; k* F. P2 v9 a
Step factor, 步长因子
7 ?! s7 v1 ~& `- Z, IStepwise regression, 逐步回归
( S" X, [ G8 m( nStorage, 存
( h) @" P, a7 S ^" pStrata, 层(复数)9 g9 ~6 y) k P4 z' H/ |
Stratified sampling, 分层抽样& ~% }: @5 q; j5 H
Stratified sampling, 分层抽样
3 p/ N$ W, w4 W- X3 PStrength, 强度
$ T1 h. t$ C& wStringency, 严密性+ E/ C- a0 r& h. U u% T* P
Structural relationship, 结构关系
0 l- V1 C0 r! H" B" \Studentized residual, 学生化残差/t化残差
; i; x3 {/ B) b; {) f0 KSub-class numbers, 次级组含量0 l, P3 p6 T/ o! t
Subdividing, 分割
. B2 |$ H' A, d& xSufficient statistic, 充分统计量+ S: h" u. t' d9 l- N2 Y; A
Sum of products, 积和 O( z3 L9 L' ~1 B' d* z
Sum of squares, 离差平方和
! G+ |% }5 R6 C$ m3 xSum of squares about regression, 回归平方和& }9 |# ~/ {6 B' o5 v2 W- \; I+ g M
Sum of squares between groups, 组间平方和
! e5 A" Q- q8 I' z$ ~Sum of squares of partial regression, 偏回归平方和
! {/ ]% ? t) \* Q# OSure event, 必然事件
" t0 `4 l0 B( r- ~+ c8 }Survey, 调查
! L; _+ H/ m2 l, l6 N) K2 ASurvival, 生存分析* F8 \ n0 @, `1 q1 \$ y2 i
Survival rate, 生存率
4 h2 u1 Y% C( D! ~$ B4 VSuspended root gram, 悬吊根图
8 ~ E* c* A5 }Symmetry, 对称
" U/ G4 |/ O. e+ r0 m" |Systematic error, 系统误差
9 c* v( }: ?- S: A, G: E8 c- e: @Systematic sampling, 系统抽样
6 z( }2 a% p% p9 e7 UTags, 标签
9 ]" Y8 q8 w8 m" j: pTail area, 尾部面积; h: B" n% F) w u
Tail length, 尾长
7 _/ W* ]# u: k6 g3 W( nTail weight, 尾重
, n- C3 e9 v$ ~Tangent line, 切线1 w, s) V0 j3 Z2 d
Target distribution, 目标分布. `& I4 ?- Z* A. {, O$ `
Taylor series, 泰勒级数3 f" U. \1 t9 u, o! s
Tendency of dispersion, 离散趋势1 s6 Z# Z# _% W! A; o
Testing of hypotheses, 假设检验( A0 \+ y2 T! |! h& }
Theoretical frequency, 理论频数
; j! Y, g8 g c$ @! RTime series, 时间序列$ P( j5 J2 L7 Y: _, H
Tolerance interval, 容忍区间
0 t9 {3 B& o% V1 w. xTolerance lower limit, 容忍下限- C# A K. E+ E. I5 {
Tolerance upper limit, 容忍上限
6 Y; J+ G1 K$ rTorsion, 扰率
& j. [. V0 P+ L6 G/ o2 W, kTotal sum of square, 总平方和
- H3 j# K# d' W& jTotal variation, 总变异6 i$ r' P4 m* @. d4 E
Transformation, 转换9 d U3 X. v0 `( R5 a
Treatment, 处理! |% x+ u5 A( E: {( @
Trend, 趋势 D' [, q8 e* K) R3 B! P) r
Trend of percentage, 百分比趋势
R5 b. t2 I/ ] P* d+ m& I R3 eTrial, 试验 G" l$ W- G7 M% n. H1 v
Trial and error method, 试错法8 {; k3 a7 } |7 z8 X: H' |- x
Tuning constant, 细调常数
7 b& |( ]$ N4 Q4 ~1 z0 eTwo sided test, 双向检验
5 j3 R, `' j9 eTwo-stage least squares, 二阶最小平方+ i. V3 O& b0 ?
Two-stage sampling, 二阶段抽样! g+ `" W- v, C n6 U
Two-tailed test, 双侧检验. i3 ^7 y ~* J
Two-way analysis of variance, 双因素方差分析
9 f6 U+ k) e/ G5 O: C: X* R' @8 nTwo-way table, 双向表9 h" W5 A4 n* v$ n7 k$ B! N1 Y
Type I error, 一类错误/α错误
+ X( h: O6 a: r4 t# _% R9 zType II error, 二类错误/β错误
! E6 [ I: b% p2 x- S) xUMVU, 方差一致最小无偏估计简称' I8 w! ~) a e! w
Unbiased estimate, 无偏估计
! P8 i0 t5 D2 Z/ k) ~: ]" z1 dUnconstrained nonlinear regression , 无约束非线性回归
: O- e, X9 X9 L: A1 B' X0 sUnequal subclass number, 不等次级组含量
- V3 R: X6 z# c2 _Ungrouped data, 不分组资料6 P- D: T5 C' y. ]( d
Uniform coordinate, 均匀坐标" {: p9 K/ C- ]+ L
Uniform distribution, 均匀分布
* E, }4 d2 O3 n0 \ Q$ mUniformly minimum variance unbiased estimate, 方差一致最小无偏估计9 _0 m: ~! H9 x) f+ F H! c5 F) \
Unit, 单元
& L" K2 _5 Z X; D; k/ ]Unordered categories, 无序分类+ k$ S" S5 \; N" l) ?/ H1 i
Upper limit, 上限3 ?1 q- a% b# D0 r
Upward rank, 升秩% L8 f7 t* ?& D/ z k
Vague concept, 模糊概念- d/ a4 ~# A9 Q) O
Validity, 有效性1 m8 V9 g0 k' v* {1 P3 O
VARCOMP (Variance component estimation), 方差元素估计& Z6 g- e0 h9 H4 a, Y- d1 ?$ i
Variability, 变异性+ z$ Q5 Q S; _0 p
Variable, 变量7 J7 ^; F' _1 ?8 {0 l
Variance, 方差& _2 Z& S! B0 B
Variation, 变异
/ ]9 Z/ J. t4 p5 n; U6 mVarimax orthogonal rotation, 方差最大正交旋转' f9 o9 r2 {( N3 y6 d+ ^8 e6 q
Volume of distribution, 容积
# O! g0 A- v3 s7 x; ^8 jW test, W检验
! J: ?* w/ i- `) C3 G3 NWeibull distribution, 威布尔分布* I, |$ G9 G( b' O9 ]
Weight, 权数+ K4 ^" q S8 N7 k) t" w
Weighted Chi-square test, 加权卡方检验/Cochran检验2 X0 q) h! `, q8 M; H1 T
Weighted linear regression method, 加权直线回归4 L5 F( e% k9 [
Weighted mean, 加权平均数
! j$ O& s& _- K; sWeighted mean square, 加权平均方差
% x# u& f4 P$ c+ i" O& Z. ? TWeighted sum of square, 加权平方和9 V* q) G. c0 r {+ M. R. w
Weighting coefficient, 权重系数" j7 x$ J1 D: G s- h
Weighting method, 加权法
2 g' p; @0 L! v* }W-estimation, W估计量
5 {) B+ q! F% n- k* v9 }W-estimation of location, 位置W估计量
" X: h/ Q6 P: mWidth, 宽度
1 g" s" m9 `+ G- v4 e6 Y$ c7 IWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
* P# H3 w6 f9 |- @4 v, lWild point, 野点/狂点/ F; d' ?. m' n0 D% j* X' ~
Wild value, 野值/狂值
* J# {, g9 i0 p+ F, v3 X% CWinsorized mean, 缩尾均值
1 c5 ?: f" B9 H+ x$ u* r: hWithdraw, 失访
5 Q a- A# @% ^/ N" t0 H& PYouden's index, 尤登指数& I+ C" [7 Z' M. c
Z test, Z检验
; v; r; Y" x6 S3 E+ [/ e& }* bZero correlation, 零相关' _( B" a9 S# _
Z-transformation, Z变换 |
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